Japanese and Chinese Immigrant Activists: Organizing in American and International Communist Movements, 1919-1933. By Josephine Fowler. (New Brunswick: Rutgers University Press, 2007. xvi, 272 pp. Cloth, $70.00, ISBN 978-0-8135-4040-5. Paper, $27.95, ISBN 978-0-8135-4041-2.)
Bibliographic record
Abstract
In Japanese and Chinese Immigrant Activists, Josephine Fowler sets out to write a broad transnational history that meaningfully integrates leftist Japanese and Chinese migrants into fields from which they have been traditionally excluded, especially the histories of American Communism and Asian America. Working “at the intersection of several interdisciplinary fields,” Fowler examines a broad range of topics, from questions of agency to both practical and theoretical inquiries about space, identity, race, gender, and nation (p. 3). The author grounds her work in transnational approaches increasingly popular with historians of labor, immigration, and Asian Americans to write a detailed study focused on the role of Chinese and Japanese migrants in creating and sustaining networks that facilitated the flow of people and ideas across national boundaries in North America, Europe, and Asia. While Fowler acknowledges the continued power of the nation-state, she rightfully insists on a broader examination of activists, information, and ideology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".